This invention relates to an application of image processing and pattern recognition, and more particularly to a method of extracting a characteristic figure from a color picture, where the characteristic figure is superimposed on a background which has a different color from that of the characteristic figure.
For extracting a characteristic figure from a color picture when the characteristic figure is superimposed on a background which has a different color from that of the characteristic figure, for example, for extracting a fingerprint or an image of a stamp printed on a color print, there is a conventional simple method of processing by a threshold level. A pixel in a color picture is usually represented by intensities of the three color components, that is R (red), G (green), B (blue) components. These values of a pixel are converted to an attribute of the pixel, for example, lightness or saturation, and all the pixels in the picture are classified into groups in accordance with the level of the attribute. For example, a pixel having an attribute level larger than a threshold level .theta. is classified as belonging to a group A, and a pixel having an attribute level not larger than the threshold level is classified as belonging to group B.
A group of pixels having the same attribute level in an area make up a characteristic figure.
Further, a background density reduction process is another method applicable when the background picture in the corresponding area is known. In this process, each pixel value of an input picture is converted to a density (scaler darkness of the pixel) and each pixel value of the background picture in the corresponding area is also converted to a density. At each pixel, the density level of the background picture is subtracted from that of the color picture for extracting the characteristic figure.
When a characteristic figure of a single color is superimposed on a background picture composed of plural areas having different colors, the resultant color of the characteristic figure becomes different on each different area of the plural areas, resulting in non-uniform attribute values of pixels in the characteristic figure. As such, the method of processing by a threshold level cannot be advantageously applied.
Although the background density reduction process has a high precision in extraction, it is unusual that the background picture is known, and the chance for applying this process is rather small.